Safety Monitoring Data Reconstruction Based On Distributed Compressive Sensing In Metro Construction

In the process of subway construction, it is necessary to obtain the accurate monitoring data for construction safety and risk assessment. However, due to the complexity of subway construction environment, the constraint of current management regulatory and the traditional way of manual data collection, most of the original data is incomplete or noisy, thus it cannot be directly used for risk assessment and decision analysis. Distributed Compressive Sensing(DCS), developed based on compressive sensing, is used for compression and reconstruction for multi-signal. Compared with other data reconstruction methods, the advantage of the DCS is that it makes full use of the correlations between inter-signal and intra-signal.This article mainly studies DCS-based field monitoring data joint reconstruction of ground settlements in metro construction. Firstly, the sparsity and relevance of the ground settlement field monitoring data is analyzed to determine whether it meets the applicable condition of DCS. Secondly, Joint Sparse Model(JSM) is built for the monitoring data by applying DCS, and an appropriate reconstruction algorithm is selected. Then the JSM is used for the offline reconstruction and online prediction of the ground settlement monitoring data. The experiment results are compared to regression analysis method, Robust Principal Component Analysis(RPCA) and Sparse Modeling Software(SPAMS). Finally, the sampling frequency of ground settlement is estimated based on DCS when sampling at random.The experimental results show that for the field monitoring data reconstruction of ground settlement in metro construction, the reconstruction precision of DCS is higher than regression analysis, RPCA, and SPAMS method. Additionally, the more relevant signals there are in the joint sparse model, the smaller the reconstruction error is. This convinces that the accuracy of signal reconstruction is improved by DCS due to the correlations between inter- and intra-signal is exploited. When sampling at random, according to a given monitoring accuracy, DCS-based sampling frequency estimation of ground settlements can provide a lower monitoring limit than actual sampling frequency.